Search Results for "kernel-module-ntfs"
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Showing 40 open source projects for "kernel-module-ntfs"
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
...We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations. -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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The PDL module gives standard perl the ability to COMPACTLY store and SPEEDILY manipulate the large N-dimensional data sets that are the bread and butter of scientific computing.
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Netgen Mesh Generator
NETGEN is an automatic 3d tetrahedral mesh generator
NETGEN is an automatic 3d tetrahedral mesh generator. It accepts input from constructive solid geometry (CSG) or boundary representation (BRep) from STL file format. The connection to a geometry kernel allows the handling of IGES and STEP files. NETGEN contains modules for mesh optimization and hierarchical mesh refinement. Netgen is open source based on the LGPL license. It is available for Unix/Linux and Windows. -
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libirt
The new site is at http://psychometricon.net/libirt/
The new site is at http://psychometricon.net/libirt/ Library of functions to estimate the items and abilities from the responses of subjects to a questionnaire. The IRT models supported are the logistic model, the multivariate logistic model, the graded model and smoothing by penalization and kernel. -
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Simple Python Fixed-Point Module
Pure-python binary fixed-point arithmetic library
This Python module provides basic facilities for mathematics on fixed-point numbers. The number of fractional binary digits is tunable, allowing near-arbitrary precision arithmetic. Arithmetic & functions such as sqrt, exp, log, sin & cos are available. For the latest releases please visit https://github.com/rwpenney/spfpm -
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erf
error function and related functions in pure standard Fortran 2008
Fortran 2008 added 3 new intrinsic functions: erf, erfc, erfc_scaled. However, they take only real arguments. This package provides a BSD licensed Fortran 2008 module with erf(z), where z is a complex argument. The calculation is based on calculating w(z), the Faddeyeva (plasma dispersion) function. Two algorithms are implemented: TOMS 680 and 916, http://www.netlib.org/toms/. The simple test program calculates values in the Abramowitz, Stegun. -
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runjags
The 'runjags' R package and standalone JAGS extension module
This package provides high-level interface utilities for MCMC models via Just Another Gibbs Sampler (JAGS), facilitating the use of parallel (or distributed) processors for multiple chains, automated control of convergence and sample length diagnostics, and evaluation of the performance of a model using drop-k validation or against simulated data. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. A JAGS extension module provides additional distributions including the Pareto family of distributions, the DuMouchel prior and the half-Cauchy prior. -
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Opt4J
Modular Java framework for meta-heuristic optimization
...The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. For this purpose, Opt4J relies on a module-based implementation and offers a graphical user interface for the configuration as well as a visualization of the optimization process. -
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riboshape
Predicting ribosome footprint profile shapes from transcript sequences
Riboshape is a suite of algorithms to predict ribosome footprint profile shapes from transcript sequences. It applies kernel smoothing to codon sequences to build predictive features, and uses these features to builds a sparse regression model to predict the ribosome footprint profile shapes. Reference: Liu, T.-Y. and Song, Y.S. Prediction of ribosome footprint profile shapes from transcript sequences. Proceedings of ISMB 2016, Bioinformatics, Vol. 32 No. 12 (2016) i183-i191. -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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Adaptive Gaussian Filtering
Machine learning with Gaussian kernels.
Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. -
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wmtsa-python
Discrete wavelet methods for time series analysis using python
...However, none of them, or at least none that I know, is aimed at scientific use. This library aims at filling this gap, in particular considering discrete wavelet transform as described by Percival and Walden. This module started as translation of the wmtsa Matlab toolbox (http://www.atmos.washington.edu/~wmtsa/), so most naming conventions and most of the code structure follows their choices. The code uses a mix of python and cython for improved performance. The code reflects my needs and preferences, but contributions from others are welcome. The code has to some extent been tested, but bugs are to be expected. -
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pyL1min
General purpose norm-1 minimization solver in Python
...You need to install Python, NumPy/SciPy and CVXOPT ( FFTW enabled) to use this software. The test.py program demonstrates a simple application in Compressive Sensing and shows how to use l1min module. You need to install matplotlib to plot diagrams. Note: pyL1min can handle complex as well as real vectors. -
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FluxModules
Module Computation for Metabolic Networks
Genome Scale Metabolic Networks are complex systems, Modules help to break them down and hence ease understanding and algorithmic complexity. FluxModules is a toolbox with code for module detection and module visualization. -
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PyGAO
Genetic Algorithm Optimization for Python
...Eventually, I will expand to more generic data structures and add multiple-species search options. For the time being, I have no plans of developing a GUI. For now, this is strictly a computational module. In addition to the standard Python libraries, PyGAO uses numpy. -
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EnvStats
An R Package for Environmental Statistics
EnvStats is an R package for environmental statistics. It is the open-source successor to the commercial module for S-Plus© called "EnvironmentalStats for S-Plus", which was first released in April, 1997. The EnvStats package, along with the R software environment, provides comprehensive and powerful software for environmental data analysis. EnvStats brings the major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. ... -
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statspy
Python module for statistics built on top of NumPy/SciPy
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A module containing python wrappers for the SUite of Non-linear DIfferential/ALgebraic Solvers (SUNDIALS), using ctypes.
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ViennaMath
A symbolic math kernel in C++
ViennaMath provides a symbolic math kernel which can be used either for compile-time processing, or for run-time evaluation. Unlike other symbolic math implementations, ViennaMath aims at providing a fast math layer for use with numerical methods such as the finite element method (cf. ViennaFEM) -
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mlpy
Machine Learning Python
mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. -
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ViennaFEM
A finite element solver using state-of-the-art programming techniques.
ViennaFEM is a library-centric implementation of the finite element method in C++. It features a symbolic math kernel, which manipulates the strong or weak form of the problem and automatically derives the discrete form. ViennaFEM is built on top of the following libraries: ViennaMath provides the symbolic math kernel, ViennaGrid (with ViennaData) allows for a generic grid handling and quantity storage, while ViennaCL provides the linear solvers and GPU acceleration. -
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A PHP module to help perform advanced astronomical computations, such as planetary positions like those published in the astronomical almanacs.
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Computes the characters of some Demazure modules of sl2^. Namely, consider the Weyl group element w_N = ... s_0 s_1 s_0 with a total of N factors. Then we can compute the character of the Demazure module V_{w_N}(m Lambda_0).
